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Quality metrics in high-dimensional data visualization : An overview and systematization

Quality metrics in high-dimensional data visualization : An overview and systematization

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BERTINI, Enrico, Andrada TATU, Daniel KEIM, 2011. Quality metrics in high-dimensional data visualization : An overview and systematization. In: IEEE Transactions on Visualization and Computer Graphics. 17(12), pp. 2203-2212. ISSN 1077-2626. eISSN 1941-0506. Available under: doi: 10.1109/TVCG.2011.229

@article{Bertini2011-12Quali-19047, title={Quality metrics in high-dimensional data visualization : An overview and systematization}, year={2011}, doi={10.1109/TVCG.2011.229}, number={12}, volume={17}, issn={1077-2626}, journal={IEEE Transactions on Visualization and Computer Graphics}, pages={2203--2212}, author={Bertini, Enrico and Tatu, Andrada and Keim, Daniel} }

<rdf:RDF xmlns:dcterms="http://purl.org/dc/terms/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bibo="http://purl.org/ontology/bibo/" xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:void="http://rdfs.org/ns/void#" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > <rdf:Description rdf:about="https://kops.uni-konstanz.de/rdf/resource/123456789/19047"> <dc:creator>Tatu, Andrada</dc:creator> <dcterms:issued>2011-12</dcterms:issued> <dc:language>eng</dc:language> <bibo:uri rdf:resource="http://kops.uni-konstanz.de/handle/123456789/19047"/> <dc:creator>Keim, Daniel</dc:creator> <dcterms:rights rdf:resource="http://nbn-resolving.org/urn:nbn:de:bsz:352-20140905103605204-4002607-1"/> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2012-04-18T10:38:13Z</dc:date> <dcterms:title>Quality metrics in high-dimensional data visualization : An overview and systematization</dcterms:title> <dc:contributor>Tatu, Andrada</dc:contributor> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dc:contributor>Bertini, Enrico</dc:contributor> <dc:rights>deposit-license</dc:rights> <dcterms:abstract xml:lang="eng">In this paper, we present a systematization of techniques that use quality metrics to help in the visual exploration of meaningful patterns in high-dimensional data. In a number of recent papers, different quality metrics are proposed to automate the demanding search through large spaces of alternative visualizations (e.g., alternative projections or ordering), allowing the user to concentrate on the most promising visualizations suggested by the quality metrics. Over the last decade, this approach has witnessed a remarkable development but few reflections exist on how these methods are related to each other and how the approach can be developed further. For this purpose, we provide an overview of approaches that use quality metrics in high-dimensional data visualization and propose a systematization based on a thorough literature review. We carefully analyze the papers and derive a set of factors for discriminating the quality metrics, visualization techniques, and the process itself. The process is described through a reworked version of the well-known information visualization pipeline. We demonstrate the usefulness of our model by applying it to several existing approaches that use quality metrics, and we provide reflections on implications of our model for future research.</dcterms:abstract> <foaf:homepage rdf:resource="http://localhost:8080/jspui"/> <dc:creator>Bertini, Enrico</dc:creator> <dcterms:bibliographicCitation>First publ. in: IEEE Transactions on Visualization and Computer Graphics ; 17 (2011), 12. - pp. 2203-2212</dcterms:bibliographicCitation> <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/rdf/resource/123456789/36"/> <dc:contributor>Keim, Daniel</dc:contributor> <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/rdf/resource/123456789/36"/> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2012-04-18T10:38:13Z</dcterms:available> </rdf:Description> </rdf:RDF>

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